In order to support the growing number of mobile communications devices, service assurance or customer experience assurance (CEA) is become increasingly important for Communications Service Providers (CSPs) to ensure that services offered over networks meet a pre-defined service quality level for an optimal subscriber experience. CEA enables CSPs to identify faults in the network and resolve these issues in a timely manner so as to minimize service downtime. In addition, CEA may include implementing policies and processes to proactively pinpoint, diagnose, and resolve service quality degradations or device malfunctions before subscribers are impacted.
Conventional solutions are challenged to provide real time and scalable solutions that meet the demands of current network volume and traffic analysis. Some conventional processes involve installing expensive, large, and complex hardware probes at aggregate network nodes to be able to better detect service and traffic degradations. Furthermore some conventional monitoring techniques may sample data packets as they arrive, typically based on random sampling techniques, so only a fraction of the packets may be examined. While helpful, such approaches are limited and may not allow accurate detection and characterization of a network and its service performance and usage. In addition, some conventional systems simply cannot scale for current volume of traffic and therefore are inadequate to identify any key trends and issues or provide visibility for efficient analysis of performance data.
In view of the foregoing, it may be understood that there may be significant problems and shortcomings associated with current solutions and technologies for monitoring communication networks and service assurance, and more particularly, for efficiently and effectively providing visualization and analysis of performance data.